Computing-device management device, computing-device management method, and computing-device management program

ABSTRACT

A computing-device management device capable of easily carrying out load distribution is provided. The computing-device management device has: a future load prediction unit that calculates a load prediction value, which is a value of a future load in each of computing devices, on the basis of load information of the computing device informed by the computing device and that determines whether the load prediction value exceeds a predetermined threshold value or not; a software allocation unit that detects, as a target computing device to be in an overloaded state in future, the computing device determined by the future load prediction unit to have the load prediction value exceeding the predetermined threshold value and that determines which computing device is to be an allocation destination of at least one software component operating in the target computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and an informing unit that informs the target computing device and the allocation-destination computing device of information of the allocated software component.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on Japanese Patent Application No.2009-289805, the contents of which are incorporated herein by reference.

TECHNICAL FIELD

The present invention relates to load prediction and load distributionof a computing-device system installed in a control station of, forexample, airplanes.

BACKGROUND ART

Conventionally, a load distribution method of monitoring the load of acomputing device and, if the load is increased, causing anothercomputing device to execute the process thereof has been known (forexample, see Patent Literature 1) as a method for improving theusability of a computing-device system.

CITATION LIST Patent Literature {PTL 1}

-   Japanese Unexamined Patent Application, Publication No. 2008-15950

SUMMARY OF INVENTION Technical Problem

However, the above described invention of Patent Literature 1 hasproblems, for example, processes become too complex to carry out theprocess of load distribution in real-time since the load of applicationsoftware is monitored on the basis of the information such as theprocess time, process start time, and process due of the individualapplication software, and load distribution is carried out on the basisof that.

The present invention has been accomplished in order to solve the abovedescribed problem, and it is an object of the present invention toprovide a computing-device management device and a computing-devicemanagement system capable of easily carrying out load distribution ofcomputing devices.

Solution to Problem

In order to solve the above described problem, the present inventionemploys the following solutions.

A first aspect of the present invention is a computing-device managementdevice connected to a plurality of computing devices via an informationtransmission medium, the computing-device management device having: afuture load prediction unit that calculates a load prediction value,which is a value of a future load in each of the computing devices, onthe basis of load information of the computing device informed by thecomputing device and that determines whether the load prediction valueexceeds a predetermined threshold value or not; a software allocationunit that detects, as a target computing device to be in an overloadedstate in future, the computing device determined by the future loadprediction unit to have the load prediction value exceeding thepredetermined threshold value and that determines which computing deviceis to be an allocation destination of at least one software componentoperating in the target computing device on the basis of a CPU load, amemory used volume, and a data communication volume of the computingdevice; and an informing unit that informs the target computing deviceand the allocation-destination computing device of information of theallocated software component.

According to such a configuration, the future load is predicted for eachof the computing devices on the basis of the CPU load, the memory usedvolume, and the data communication volume of the computing deviceinstead of the state of the applications operating on the computingdevice. Therefore, the future working state of the computing devices canbe easily predicted. Furthermore, the software component working in thecomputing device which is determined to be in the overloaded state inthe future can be transferred to another computing device before thecomputing device becomes the overloaded state; therefore, the computingdevices can be prevented from becoming the overloaded state. As aresult, the usability of the computing devices can be improved.

The above described computing-device management device may be configuredso that, when one software component is operating in an active state inone of the computing devices, another software component that is thesame as the one software component is operated in a standby state in atleast another one of the computing devices; and the software allocationunit determines which computing device is to be the allocationdestination of the software component to be operated in the active stateand which computing device is to be the allocation destination of thesoftware component to be operated in the standby state.

In this manner, in the allocation of the software component, thecomputing device in which the software component to be operated in theactive state and the computing device in which the software component isto be operated in the standby state are determined. Therefore, thesoftware component can be always caused to be duplex. As a result, theusability of the computing-device system can be further improved.

The above described computing-device management device may be configuredso that the software allocation unit calculates a transfer score foreach of the software component on the basis of: loads of a CPU load, amemory load, and a data communication volume of the software componentoperating on the target computing device; predetermined weight factorsfor the CPU load, the memory load, and the data communication volume;and a transfer priority set for each of the software component; and thesoftware allocation unit prioritizes allocation of the softwarecomponent having a large score as the transfer score to the othercomputing device.

In this manner, the transfer score which is the index of the loadapplied to the computing device is calculated about each softwarecomponent operating on the computing device determined to be in theoverloaded state, and the software component having a higher transferscore is prioritized for selection of the allocation-destinationcomputing device. As a result, transfer of the software component havinga low degree of real-time processing demand and the software componenthaving a large load to another computing device can be prioritized, theinfluence of process interruption of the computing device caused alongwith transfer of the software component can be reduced, and the load ofthe computing device which is determined to be in the overloaded statein the future can be efficiently reduced.

The above described computing-device management device may be configuredso that the future load prediction unit calculates the load predictionvalue by using a mathematical-equation model using past load informationof the computing device as one of parameters.

In this manner, the future load to be applied to the computing devicescan be predicted on the basis of the past load information of thecomputing devices. Therefore, future load prediction further close toreality can be carried out, and the precision of the future loadprediction can be improved. The above described mathematical model is,for example, Lagrange interpolation polynomials.

The above described computing-device management device may be configuredso that the future load prediction unit calculates the load predictionvalue of each of the computing devices on the basis of the CPU load, thememory used volume, and the data communication volume of the computingdevice.

In this manner, the future loads applied to the computing devices arepredicted on the basis of the CPU loads, the memory loads, and the datacommunication volumes of the computing devices. Therefore, the workingstate of the computing devices can be understood in detail, and theprecision of the load distribution can be improved.

A second aspect of the present invention is a computing-devicemanagement device connected to a plurality of computing devices via aninformation transmission medium, the computing-device management devicehaving: a fault monitoring unit that detects the computing device inwhich a fault has been occurring on the basis of fault occurrenceinformation informed by the computing device; a software allocation unitthat determines which computing device is to be an allocationdestination of a software component operated on the fault-occurrencedetected computing device on the basis of a CPU load, a memory usedvolume, and a data communication volume of the computing device; and aninforming unit that informs the allocation-destination computing deviceof information of the allocated software component.

According to such a configuration, the occurrence of faults in thecomputing devices is monitored on the basis of the fault informationinformed by the computing devices; and, if the computing device in whicha fault is occurring is detected, the allocation of the softwarecomponents operated in the fault-occurred computing device is carriedout. Therefore, switching of the allocation of the software componentscan be promptly carried out. As a result, the usability of thecomputing-device system can be improved.

The computing-device management device according to the first aspect orthe second aspect may be configured so that the software allocation unitcalculates a weighted future load for each of the computing devices onthe basis of load prediction values respectively calculated for the CPUload, the memory load, and the data communication volume of thecomputing device and predetermined weight factors for the CPU load, thememory load, and the data communication volume; and allocation of thesoftware component to the computing device having a small load as theweight future load is prioritized.

In this manner, the weighted future load is calculated for each of thecomputing devices on the basis of the load prediction values calculatedrespectively for the CPU load, the memory load, and the datacommunication volume of each of the computing devices and thepredetermined weight factors for the CPU load, the memory load, and thedata communication volume. The weighted future load is an indexindicating that the smaller the value, the smaller the future load inthe computing device. Therefore, the software component can be executedby the computing device having a small future load by prioritizingselection of the computing device having a small load as the weightedfuture load as the computing device of the allocation destination of thesoftware component. As a result, load distribution can be efficientlycarried out, and the usability of the computing-device system can beimproved.

A third aspect of the present invention is a computing-device managementsystem having a plurality of computing devices and the computing-devicemanagement device according to the first aspect or the second aspect.

The above described computing-device management system may be configuredso that the computing-device management device is duplex.

Since the computing-device management device is duplex, even when thecomputing-device management device operating in the active state fails,the second computing-device management device is operated. Therefore,the computing-device management system per se can be continuouslyoperated.

A fourth aspect of the present invention is a computing-devicemanagement method including: a step of calculating a load predictionvalue, which is a value of a future load in each of computing devices,on the basis of load information of the computing device informed by thecomputing device and determining whether the load prediction valueexceeds a predetermined threshold value or not; a step of detecting, asa target computing device to be in an overloaded state in future, thecomputing device determined to have the load prediction value exceedingthe predetermined threshold value by the step of determining whether theload prediction value exceeds the predetermined threshold value or notand determining which computing device is to be an allocationdestination of at least one software component operating in the targetcomputing device on the basis of a CPU load, a memory used volume, and adata communication volume of the computing device; and a step ofinforming the target computing device and the allocation-destinationcomputing device of information of the allocated software component.

A fifth aspect of the present invention is a computing-device managementprogram for causing a computer to execute: a process of calculating aload prediction value, which is a value of a future load in each ofcomputing devices, on the basis of load information of the computingdevice informed by the computing device and determining whether the loadprediction value exceeds a predetermined threshold value or not; aprocess of detecting, as a target computing device to be in anoverloaded state in future, the computing device determined to have theload prediction value exceeding the predetermined threshold value by theprocess of determining whether the load prediction value exceeds thepredetermined threshold value or not and determining which computingdevice is to be an allocation destination of at least one softwarecomponent operating in the target computing device on the basis of a CPUload, a memory used volume, and a data communication volume of thecomputing device; and a process of informing the target computing deviceand the allocation-destination computing device of information of theallocated software component.

A sixth aspect of the present invention is a computing-device managementmethod including: a step of detecting the computing device in which afault has been occurring on the basis of fault occurrence informationinformed by the computing device; a step of determining which computingdevice is to be an allocation destination of a software componentoperated on the fault-occurrence detected computing device on the basisof a CPU load, a memory used volume, and a data communication volume ofthe computing device; and a step of informing the allocation-destinationcomputing device of information of the allocated software component.

A seventh aspect of the present invention is a computing-devicemanagement program for causing a computer to execute: a process ofdetecting the computing device in which a fault has been occurring onthe basis of fault occurrence information informed by the computingdevice; a process of determining which computing device is to be anallocation destination of a software component operated on thefault-occurrence detected computing device on the basis of a CPU load, amemory used volume, and a data communication volume of the computingdevice; and a process of informing the allocation-destination computingdevice of information of the allocated software component.

Advantageous Effects of Invention

According to the present invention, load distribution of computingdevices can be easily carried out.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a functional block diagram showing an example of theconfiguration of a computing-device system according to a firstembodiment of the present invention.

FIG. 2 is a graph for explaining a method of calculating a future loadby Lagrange interpolation polynomials.

FIG. 3 is a diagram for explaining a method of selecting a softwarecomponent.

FIG. 4 is a diagram for explaining a method of selecting a computingdevice in which the software component is to be operated.

FIG. 5 is a diagram showing a flow chart of a computing-devicemanagement method according to the first embodiment of the presentinvention.

FIG. 6 is a functional block diagram showing an example of theconfiguration of a computing-device system according to a secondembodiment of the present invention.

DESCRIPTION OF EMBODIMENTS

Hereinafter, embodiments of computing-device management devices of thepresent invention will be explained in detail sequentially from [FirstEmbodiment] to [Second Embodiment] with reference to drawings.

First Embodiment

FIG. 1 is a functional block diagram showing a brief configuration of acomputing-device management system according to the present embodiment.

As shown in FIG. 1, a computing-device system 20 according to thepresent embodiment has a plurality of computing devices 3, 4, and 5 anda computing-device management device 1. The computing devices 3, 4, and5 and the computing-device management device 1 are mutually connectedvia an information transmission medium 2 and configured to be able tocarry out bidirectional communication therebetween.

In the computing-device system 20, common software components areinstalled in a plurality of computing devices. When one softwarecomponent is operating in an active state in one computing device,another software component that is the same as the one softwarecomponent is always operating in a standby state in at least one othercomputing device. The active state is a state in which the softwarecomponent is working. On the other hand, the standby state is apreparation state in which the software component is normally waiting asa backup component in order to promptly continue operation in place ofthe active state when the component that is in the active state becomesunusable or is stopped.

Furthermore, the computing device, in which a software component isoperating in the active state, periodically informs the computingdevice, in which the same software component is operating in the standbystate, of the information retained by the software component that isoperating in the active state. Therefore, the information retained amongthe software component that is operating in the active state and thesoftware component that is operating in the standby state are the same.When the same software component is installed in the plurality ofcomputing devices and caused to operate in the active state and thestandby state in this manner, redundancy can be ensured, and theswitching of the computing device in which the software component is tobe operated in the active state can be promptly carried out.

As shown in FIG. 1, the present embodiment presupposes the state inwhich: both a software component A and a software component B areoperating in the active state in the computing device 3, the softwarecomponent A is operating in the standby state in the computing device 4,and the software component B is operating in the standby state in thecomputing device 5.

Each of the computing devices 3, 4, and 5 has a common processing unit11. The common processing unit 11 periodically monitors the CPU load,the memory used volume, and the data communication volume of thecomputing device, in which the unit is provided, and informs thecomputing-device management device 1 of load information 201 which isthe results of the monitoring.

Furthermore, when the common processing unit 11 is informed of a stopinstruction 205 by the computing-device management device 1, withrespect to a corresponding software component operating on the computingdevice thereof, the common processing unit 11 carries out a process ofstopping the software component in accordance with the instruction. Whenthe common processing unit 11 is informed of a generation instruction203 by the computing-device management device 1, the common processingunit 11 carries out a process of generating a software component inaccordance with the instruction.

The computing-device management device 1 has: a future load predictionunit 7, a software allocation unit 8, and an informing unit 9.

The future load prediction unit 7 calculates load prediction values,which are the values of the future loads of the computing devices 3, 4,and 5, on the basis of load information 201 of the computing devicesinformed by the computing devices 3, 4, and 5; and the future loadprediction unit 7 determines whether the load prediction values exceedpredetermined threshold values or not. If there is any computing devicehaving the load prediction value exceeding the predetermined thresholdvalue, it is determined that the computing device will be in anoverloaded state in the future, and the information of the computingdevice is output to the software allocation unit 8.

Specifically, the load prediction values are calculated by predeterminedarithmetic equations by using the load information 201 informed by thecomputing devices 3, 4, and 5 and past load information 200 which is theload information 201 the future load prediction unit 7 is previouslyinformed of and saved by the future load prediction unit 7. Thearithmetic equations are, for example, interpolation polynomials.

More specifically, the future load prediction unit 7 calculates the loadprediction values by using Lagrange interpolation polynomials. Forexample, a future load value L (t) at future time t can be obtained byan equation (1) and an equation (2) of n-th order Lagrange interpolationpolynomials, which are publicly known mathematical equations, whereinthe time of the future for which the future load is to be calculated ist, a load measured value of the past is l_(k), load measured time of thepast is t_(k), the number of order is n.

$\begin{matrix}\left\{ {{Math}\mspace{14mu} 1} \right\} & \; \\{{L(t)} = {\sum\limits_{k = 0}^{n}\; {{L_{k}(t)}l_{k}}}} & (1)\end{matrix}$

The equation (1) is provided on the condition that the equation (2) issatisfied.

$\begin{matrix}{{L_{k}(t)} = {\prod\limits_{j = 0}^{n{({j \neq k})}}\; \frac{t - t_{j}}{t_{k - t_{j}}}}} & (2)\end{matrix}$

FIG. 2 is a graph in which a horizontal axis represents time and avertical axis represents a load rate (percent is used as the unitthereof). The load rate refers to the rate (percent is used as the unitthereof) of the CPU load, the memory used volume, or the datacommunication volume actually monitored in each computing device whenthe state in which the CPU load, the memory used volume, or the datacommunication volume of the computing device is fully used is assumed tobe 100 percent.

For example, when the order is 3 in the case in which the load ratemeasured values of the past and the load rate measured value of thecurrent time are obtained, the future load rate L (t) at future loadcalculation time t is obtained by a below equation (3) on the basis ofthe load rate measured values of the last time, the penultimate time,and the antepenultimate time. In the equation (3), the future time atwhich the future load is to be calculated is t, the load ratemeasurement time of this time to the third last time is t₀ to t₃, theload rate measured values of this time to the third last time is l₀ tol₃, a load measurement cycle is T, and the difference between the futureload calculation time and the current time is Td. The cycle T and thedifference Td are defined in a configuration definition storage unit 10and are the values which can be arbitrarily changed.

$\begin{matrix}\left\{ {{Math}\mspace{14mu} 2} \right\} & \; \\{{L(t)} = {{\frac{\left( {t - t_{1}} \right)\left( {t - t_{2}} \right)\left( {t - t_{3}} \right)}{\left( {t_{0} - t_{1}} \right)\left( {t_{0} - t_{2}} \right)\left( {t_{0} - t_{3}} \right)}l_{0}} + {\frac{\left( {t - t_{0}} \right)\left( {t - t_{2}} \right)\left( {t - t_{3}} \right)}{\left( {t_{1} - t_{0}} \right)\left( {t_{1} - t_{2}} \right)\left( {t_{1} - t_{3}} \right)}l_{1}} + {\frac{\left( {t - t_{0}} \right)\left( {t - t_{1}} \right)\left( {t - t_{3}} \right)}{\left( {t_{2} - t_{0}} \right)\left( {t_{2} - t_{1}} \right)\left( {t_{2} - t_{3}} \right)}l_{2}} + {\frac{\left( {t - t_{0}} \right)\left( {t - t_{1}} \right)\left( {t - t_{2}} \right)}{\left( {t_{3} - t_{0}} \right)\left( {t_{3} - t_{1}} \right)\left( {t_{3} - t_{2}} \right)}l_{3}}}} & (3)\end{matrix}$

For example, when the load prediction value L (t)′ of the computingdevice 3 exceeds the predetermined threshold value, the computing device3 is predicted to be in the overloaded state in the future, and theresult is output to the software allocation unit 8.

In this manner, the future load prediction unit 7 specifies thecomputing device which will be overloaded in the future. Therefore, thecomputing devices which will be likely overloaded can be detected beforethe computing devices are overloaded. The future load is predictedaccording to the CPU load, the memory used volume, and the datacommunication volume without taking applications into consideration;therefore, the future loads of the computing devices can be predictedwith the processing volume smaller than that of the case in which thefuture loads are predicted in consideration of the applications.

The software allocation unit 8 calculates a transfer score for each ofthe software components in the computing device, which is determined tobe in the overloaded state in the future, on the basis of: the loadvalues of CPU load, memory load, and data communication volume of eachsoftware component; predetermined weighting factors for the CPU load,the memory load, and the data communication volume; and a transferpriority set for each of the software components. The computing deviceto serve as an allocation destination is determined for the softwarecomponents in the descending order of the transfer score, and thesoftware allocation unit 8 outputs the result to the informing unit 9.

Specifically, as shown in FIG. 3, the current loads of the CPU load, thememory used volume, and the data communication volume are calculated foreach of the software components of the computing device 3; the CPU loadis integrated with a predetermined weight factor of the CPU load, thecurrent memory used volume is integrated with a predetermined weightfactor of the memory used volume, and the current data communicationvolume is integrated with a predetermined weight factor of the datacommunication volume; and the sum of the integration results iscalculated as the weighted load B of the software component.Subsequently, the weighted load B and a predetermined transfer priorityof the software component are integrated to calculate a transfer score.The transfer score is an index of the load applied to the computingdevice by the software component. It can be assumed that the larger thetransfer score, the larger the load applied to the computing device bythe software component.

Subsequently, the computing device to which the software component is tobe transferred is determined. Specifically, the computing device whichis to operate the software component is selected on the basis of thefuture load state of the computing devices.

More specifically, as shown in FIG. 4, the load prediction values ofeach of the computing devices calculated by the future load predictionunit 7 and the weight factor of the CPU load, the weight factor of thememory used volume, and the weight factor of the data communicationvolume stored in the configuration definition storage unit 10 areintegrated to calculate weighted future load C. The computing device foroperating the component is selected in accordance with the value of theweighted future load C. The weighted future load C is an indexrepresenting the magnitude of the future load of the computing device;and the load C means that the smaller the value thereof, the smaller thepredicted future load. Therefore, the software component can beefficiently allocated to the computing device having a small load byselecting the computing device having a small value of the weightedfuture load C as the computing device which is to operate the softwarecomponent.

For example, the future load prediction unit 7 predicts that thecomputing device 3 will be overloaded in the future, and the softwarecomponent B operated in the active state in the computing device 3 is tobe allocated to another computing device. In this case, the softwareallocation unit 8 obtains the weighted future load of each of thecomputing devices and, on the basis of the weighted future load, selectsthe computing device which is to operate the software component B, whichis operating in the active state in the computing device 3. As a result,the software component B normally operates, and the computing devicecapable of ensuring resources can be selected as the computing deviceserving as the allocation destination. In this process, it is preferredthat the computing device determined to be in the overloaded state inthe future and the computing device in which the software component inthe standby state for which redundancy is not ensured is operating beexcluded from the selection of determining the computing device tooperate the component. Therefore, in the present embodiment, thecomputing device 4 is selected as the computing device to operate thesoftware component B in the active state.

The informing unit 9 informs the computing device, which is determinedto be in the overloaded state in the future, and the computing device,which is the allocation destination of the software component, of theinformation about the allocation of the software component. For example,the informing unit 9 outputs the stop instruction 205 to the computingdevice 3, in which the software component B is operating in the activestate, and outputs the generation instruction 203 to the computingdevice 4, in which the software component B is to be newly operated inthe active state.

Information such as the initial layout of the software components, thepriorities of the software components, and the maximum allowable load ofcomputing device resources is stored in the configuration definitionstorage unit 10 in advance. Specifically, the information such as: theinitial layout of the software components representing the operatingstates (the active state and the standby state) of the softwarecomponents in the computing devices 3, 4, and 5; the priorities fortransferring the software components; and the maximum allowable loads ofthe CPU loads applied to the computing devices, the memory used volumes,and the data communication volumes is stored in advance.

Next, working of the computing-device management device according to thepresent embodiment will be explained. Herein, for convenience ofexplanation, the working will be explained on the presupposition that:the software component A and the software component B are operating inthe active state in the computing device 3, the software component A isoperating in the standby state in the computing device 4, and thesoftware component B is operating in the standby state in the computingdevice 5.

First, the common processing unit 11 of the computing device 3periodically monitors the CPU load, the memory volume, and the datacommunication volume of the computing device of its own, and themonitoring results are output to the computing-device management device1 as the load information 201.

Similarly, the monitoring results of the computing devices 4 and 5 areoutput to the computing-device management device 1 as the loadinformation 201 by the common processing units 11 of the computingdevices 4 and 5. The past load information 200 including the CPU loads,memory used volumes, and data communication volumes of the past retainedby the future load prediction unit 7 of the computing-device managementdevice 1 is read. In accordance with the past load information 200 andthe load information 201 informed by the computing devices 3, 4, and 5,the prediction load values respectively about the CPU load, memory usedvolume, and data communication volume are calculated for each of thecomputing devices. The calculated prediction load values are comparedwith predetermined threshold values. When the prediction load values arelarger than the predetermined threshold values as a result of thecomparison, the information of this computing device is output to thesoftware allocation unit 8. For example, when the prediction load valuesof the computing device 3 are larger than the threshold values, theinformation of the computing device 3 is output to the softwareallocation unit 8.

In the software allocation unit 8, the software component to betransferred is selected from among the software components A and Boperating in the computing device 3, which is determined to be in theoverloaded state in the future by the future load prediction unit 7.When the software component B is selected as a result, theallocation-destination computing device of the software component B issubsequently selected. As a result, the computing device 4 is selectedas the computing device in which the software component B is to beoperated in the active state. The information about the new allocationof the software component is output to the informing unit 9 as anallocation plan 202. As a result, the computing device 4 is informed ofthe generation instruction 203 about the software component B, and thecomputing device 3, in which the software component B has been operatedin the active state, is informed of the stop instruction 205.

In the common processing unit 11 of the computing device 4, a generationprocess 204 of generating the software component B in the active stateis executed on the basis of the generation instruction 203 obtained fromthe informing unit 9. In the common processing unit 11 of the computingdevice 3, a stop process 206 of stopping a process is executed withrespect to the software component B, which is in the active state, onthe basis of the stop instruction 205 obtained from the informing unit9. When the above described processes are executed, the softwarecomponent B in the computing device 3 is stopped, and the softwarecomponent B of the computing device 4 is operated in the active state.

In the above described embodiment, the processes carried out by hardwareserving as the computing-device management device are presupposed.However, the embodiment is not necessarily limited to such aconfiguration. For example, a configuration in which the processes arecarried out separately by software can be also implemented. In thatcase, the computing-device management device has a CPU, a main storagedevice such as a RAM, and a computer-readable recording medium in whicha program for realizing all or part of the above described processes isrecorded. The processes similar to those of the above describedcomputing-device management device are realized when the CPU reads theprogram recorded in the storage medium and executes informationprocessing/computing processes.

Herein, the computer-readable recording medium refers to, for example, amagnetic disk, magnetic optical disk, CD-ROM, DVD-ROM, or asemiconductor memory. The computer program may be delivered to acomputer by a communication line so that the computer received thedelivery executes the program.

Hereinafter, a process procedure of a computing-device management methodrealized when the computing-device management program is executed by theCPU will be explained with reference to FIG. 5.

First, each of the computing devices monitors the load information ofthe CPU load, the memory used volume, and the data communication volumeof its own computing device (step SA1 of FIG. 5). Next, future loadvalues are predicted from the monitored load information and past loadinformation (step SA2). The predicted load values are compared with thethreshold values (step SA3). When the predicted load value exceeds thethreshold value, a plan about allocation of software components isdetermined (step SA4). On the basis of the determined plan about theallocation, the computing devices serving as processing targets areinformed of instructions of processes (step SA5). The processescorresponding to the substances of the instructions informed in step SA5are carried out, and the present process is terminated (step SA6).

As described above, according to the computing-device management deviceand the computing-device management system according to the presentembodiment, the load information which is the resource information ofthe computing devices including the CPU loads, the memory used volumes,and the data communication volumes of the computing devices ismonitored, and the future load thereof is predicted in accordance withthe current load information and the past load information; as a result,the computing device which will be in the overloaded state can be easilypredicted, and allocation of the software component, which is operatingin the computing device predicted to be in the overloaded state, can bechanged to the computing device having allowance in the computing deviceresources thereof. Thus, the software component can be transferred, andthe loads applied to the computing devices can be distributed beforeproblems of the calculation system caused by the overloaded state occur.Therefore, usability and reliability as the computing-device system canbe improved.

Moreover, since the future loads are predicted in accordance with theCPU load, the memory used volume, and the data communication volumewithout taking applications into consideration, the processing volumecan be reduced compared with the case in which the future loads arepredicted in consideration of the applications.

Furthermore, the same software components are installed in the pluralityof computing devices and operated in the active state and standby state;therefore, redundancy is always ensured, and switching of the computingdevices which are to operate the components in the active state can bepromptly carried out.

In the present embodiment, the order of the polynomials is 3 uponcalculation of the load prediction value; however, the order is notlimited thereto. For example, the load rate measured values of this timeto the fourth last time may be used as the parameters for calculatingthe future load with the order of the polynomials of 4.

In the process of calculating the transfer score from the load values ofthe CPU load, the memory load, and the data communication volume of eachof the software components, the load prediction values of the CPU load,the memory load, and the data communication volume may be calculated andused instead of the load values of the CPU load, the memory load, andthe data communication volume.

Second Embodiment

The present embodiment is different from the above described firstembodiment in the point that the computing-device management systemmonitors fault occurrence of the computing devices and the allocation ofthe software components is changed in accordance with occurred faults.Hereinafter, different points of the computing-device management systemaccording to the present embodiment will be mainly explained by usingFIG. 6, wherein the explanation of the points common to the firstembodiment will be omitted.

As shown in FIG. 6, the present embodiment presupposes that: thesoftware component A and the software component B are both operated inthe active state in the computing device 3, the software component A isoperated in the standby state in the computing device 4, and thesoftware component B is operated in the standby state in the computingdevice 5. Each of the computing devices 3, 4, and 5 has a faultmonitoring unit 15, which detects occurrence of faults.

For example, when the fault monitoring unit 15 of the computing device 3detects fault occurrence in the software component A of the computingdevice 3, the fault monitoring unit 15 informs the computing-devicemanagement device 1 and the other computing devices of fault information301. Among the computing devices 3, 4, and 5, which obtained the faultinformation 301, the computing device 4 in which the software componentA operated in the fault-occurred computing device is operated in thestandby state executes a switching process 303 of switching thecorresponding software component A of its own from the standby state tothe active state. As a result, the corresponding software component A isoperated in the active state.

When the computing-device management device 1 obtains the faultinformation 301, the computing-device management device 1 selects theallocation-destination computing device in which the software componentA operated in the fault-occurred computing device is to be newlyoperated in the standby state in order to ensure redundancy. The methoddescribed in the above described first embodiment can be employed as aselection method thereof. Upon the selection, it is preferred that thecomputing device determined to be in the overloaded state in the future,the computing device in which the software component A in the activestate for which redundancy cannot be ensured is operating, and thecomputing device in which hardware may have a fault and the fault of thesoftware component A occurred be excluded from the selection ofdetermining the computing device which is to operate the component. Inthe present embodiment, the computing device 5 is selected. Thecomputing-device management device 1 newly generates the softwarecomponent A for the selected computing device 5 and outputs a generationinstruction 306 for operating the component in the standby state. Thecomputing device 5, which has received the generation instruction 306,executes a generation process 307 for operating the correspondingsoftware component A in the standby state. The computing device 3executes a termination process 302 of terminating the fault-occurredsoftware component A.

In this manner, according to the computing-device management systemaccording to the present embodiment, when occurrence of a fault isdetected, the computing device in which the software component operatedin the fault-occurred computing device is operated in the standby statepromptly switches the corresponding software component from the standbystate to the active state. As a result, even when the fault occurs,switching of the software component is promptly carried out; therefore,the process thereof can be continuously carried out. Therefore,usability and reliability of the computing-device system can beimproved.

REFERENCE SIGNS LIST

-   1 COMPUTING-DEVICE MANAGEMENT DEVICE-   2 INFORMATION TRANSMISSION MEDIUM-   3 COMPUTING DEVICE-   4 COMPUTING DEVICE-   5 COMPUTING DEVICE-   7 FUTURE LOAD PREDICTION UNIT-   8 SOFTWARE ALLOCATION UNIT-   9 INFORMING UNIT-   10 CONFIGURATION DEFINITION STORAGE UNIT-   11 COMMON PROCESSING UNIT-   15 FAULT MONITORING UNIT-   201 LOAD INFORMATION-   202 ALLOCATION PLAN-   203 GENERATION INSTRUCTION-   204 GENERATION PROCESS-   205 STOP INSTRUCTION-   206 STOP PROCESS-   301 FAULT INFORMATION-   302 TERMINATION PROCESS-   303 SWITCHING PROCESS-   306 GENERATION INSTRUCTION-   307 GENERATION PROCESS

1. A computing-device management device connected to a plurality of computing devices via an information transmission medium, the computing-device management device comprising: a future load prediction unit that calculates a load prediction value, which is a value of a future load in each of the computing devices, on the basis of load information of the computing device informed by the computing device and that determines whether the load prediction value exceeds a predetermined threshold value or not; a software allocation unit that detects, as a target computing device to be in an overloaded state in future, the computing device determined by the future load prediction unit to have the load prediction value exceeding the predetermined threshold value and that determines which computing device is to be an allocation destination of at least one software component operating in the target computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and an informing unit that informs the target computing device and the allocation-destination computing device of information of the allocated software component.
 2. The computing-device management device according to claim 1, wherein, when one software component is operating in an active state in one of the computing devices, another software component that is the same as the one software component is operated in a standby state in at least another one of the computing devices; and the software allocation unit determines which computing device is to be the allocation destination of the software component to be operated in the active state and which computing device is to be the allocation destination of the software component to be operated in the standby state.
 3. The computing-device management device according to claim 1, wherein the software allocation unit calculates a transfer score for each of the software component on the basis of: loads of a CPU load, a memory load, and a data communication volume of the software component operating on the target computing device; predetermined weight factors for the CPU load, the memory load, and the data communication volume; and a transfer priority set for each of the software component; and the software allocation unit prioritizes allocation of the software component having a large score as the transfer score to the other computing device.
 4. The computing-device management device according to claim 1, wherein the future load prediction unit calculates the load prediction value by using a mathematical-equation model using past load information of the computing device as one of parameters.
 5. The computing-device management device according to claim 1, wherein the future load prediction unit calculates the load prediction value of each of the computing devices on the basis of the CPU load, the memory used volume, and the data communication volume of the computing device.
 6. A computing-device management device connected to a plurality of computing devices via an information transmission medium, the computing-device management device comprising: a fault monitoring unit that detects the computing device in which a fault has been occurring on the basis of fault occurrence information informed by the computing device; a software allocation unit that determines which computing device is to be an allocation destination of a software component operated on the fault-occurrence detected computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and an informing unit that informs the allocation-destination computing device of information of the allocated software component.
 7. The computing-device management device according to claim 1, wherein the software allocation unit calculates a weighted future load for each of the computing devices on the basis of load prediction values respectively calculated for the CPU load, the memory load, and the data communication volume of the computing device and predetermined weight factors for the CPU load, the memory load, and the data communication volume; and allocation of the software component to the computing device having a small load as the weight future load is prioritized.
 8. A computing-device management system comprising a plurality of computing devices and the computing-device management device according to claim
 1. 9. The computing-device management system according to claim 8, wherein the computing-device management device is duplex.
 10. A computing-device management method comprising: a step of calculating a load prediction value, which is a value of a future load in each of computing devices, on the basis of load information of the computing device informed by the computing device and determining whether the load prediction value exceeds a predetermined threshold value or not; a step of detecting, as a target computing device to be in an overloaded state in future, the computing device determined to have the load prediction value exceeding the predetermined threshold value by the step of determining whether the load prediction value exceeds the predetermined threshold value or not and determining which computing device is to be an allocation destination of at least one software component operating in the target computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and a step of informing the target computing device and the allocation-destination computing device of information of the allocated software component.
 11. A computing-device management program for causing a computer to execute: a process of calculating a load prediction value, which is a value of a future load in each of computing devices, on the basis of load information of the computing device informed by the computing device and determining whether the load prediction value exceeds a predetermined threshold value or not; a process of detecting, as a target computing device to be in an overloaded state in future, the computing device determined to have the load prediction value exceeding the predetermined threshold value by the process of determining whether the load prediction value exceeds the predetermined threshold value or not and determining which computing device is to be an allocation destination of at least one software component operating in the target computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and a process of informing the target computing device and the allocation-destination computing device of information of the allocated software component.
 12. A computing-device management method comprising: a step of detecting the computing device in which a fault has been occurring on the basis of fault occurrence information informed by the computing device; a step of determining which computing device is to be an allocation destination of a software component operated on the fault-occurrence detected computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and a step of informing the allocation-destination computing device of information of the allocated software component.
 13. A computing-device management program for causing a computer to execute: a process of detecting the computing device in which a fault has been occurring on the basis of fault occurrence information informed by the computing device; a process of determining which computing device is to be an allocation destination of a software component operated on the fault-occurrence detected computing device on the basis of a CPU load, a memory used volume, and a data communication volume of the computing device; and a process of informing the allocation-destination computing device of information of the allocated software component.
 14. The computing-device management device according to claim 6, wherein the software allocation unit calculates a weighted future load for each of the computing devices on the basis of load prediction values respectively calculated for the CPU load, the memory load, and the data communication volume of the computing device and predetermined weight factors for the CPU load, the memory load, and the data communication volume; and allocation of the software component to the computing device having a small load as the weight future load is prioritized.
 15. A computing-device management system comprising a plurality of computing devices and the computing-device management device according to claim
 6. 16. The computing-device management system according to claim 15, wherein the computing-device management device is duplex. 